Berkeley News recently covered what is being described as the largest study of generative AI use among undergraduates, and I think the most interesting part is not only the cheating angle.
More than 95,000 students across 20 research-intensive public universities were surveyed. Around two-thirds said they used GenAI, almost 40% used it monthly or more, and at least 9% of AI users reported using it to cheat.
That part matters, of course. But the bigger issue may be what the study reveals about uneven access and uneven AI fluency.
Low-income students, female students, and racially underrepresented students were less likely to use AI. In a job market where AI proficiency is already becoming an advantage, that gap could become another layer of educational and professional inequality.
For universities, the challenge seems to be bigger than detecting cheating. They need to define what responsible AI use looks like in practice, update assessments so they measure real understanding, and make AI literacy accessible to all students, not only to those who already have the confidence, time, or resources to experiment with these tools. Blanket bans are becoming harder to defend and at the same time, treating AI as a neutral productivity tool is too simplistic.
This is becoming a skills issue, an ethics issue, and an access issue at the same time.
news.berkeley.edu/2026/05/21/t...
